Data Envelopment Analysis with GAMS: A Handbook on Productivity Analysis and Performance Measurement (International Series in Operations Research & Management Science) - Softcover

Emrouznejad, Ali; Petridis, Konstantinos; Charles, Vincent

Softcover

ISBN 10: 3031307038 ISBN 13: 9783031307034

Publisher: Springer, 2024

Synopsis

This book provides a comprehensive and practical introduction to Data Envelopment Analysis (DEA). It explains how this non-parametric technique is used to measure performance and extract efficiency from homogeneous entities within a production procedure. It situates DEA within a growing field of productivity analysis and performance measurement, for which numerous models have been proposed. 

This book encapsulates all of the advances in DEA models proposed in the literature. These models are presented in the context of the GAMS software, which is a powerful tool for mathematical programming models. This book serves two educational purposes: it introduces readers to DEA models and provides examples using GAMS. In addition, the reader is introduced to GAMS programming, as well as innovative and practical applications. GAMS codes are available for free, allowing readers to test and expand the models to meet their specific needs.

About this title

About the Author

Ali Emrouznejad (Professor and Chair in Business Analytics) is Director of the Centre for Business Analytics in Practice (CBAP) at Surrey Business School, UK. His areas of research interest include performance measurement and management, efficiency and productivity analysis as well as AI and big data. He holds an MSc in applied mathematics and received his PhD in operational research and systems from Warwick Business School, UK. Professor Emrouznejad is editor of Annals of Operations Research, associate editor of Socio-Economic Planning Sciences, department editor of OR-Spectrum and IMA journal of Management Mathematics, and member of editorial boards or guest editor in several other scientific journals including European Journal of Operational Research and Journal of Operational Research Society. He has published over 250 articles in top ranked journals. He is author of the book on “Applied Operational Research with SAS”, and editor of several other books including “Performance Measurement with Fuzzy DEA”, “Managing Service Productivity” and “Handbook of Research on Strategic Performance Management and Measurement Using DEA”. He is also founder of www.DEAzone.com and co-founder of Performance Improvement Management Software (PIM-DEA  www.DEAsoftware.co.uk).

Konstantinos Petridis is Research Assistant in University of Macedonia. He holds a B.Sc. in Mathematics from the Aristotle University of Thessaloniki, a M.Sc. in Logistics Management from Department of Economic Sciences, Aristotle University of Thessaloniki while his Ph.D. thesis was focused on Operational Research with application to natural resources. His research interests include the study and modeling of production and distribution of biomass and natural resources systems, supply chain management design and sustainability through the use of operational research and performance measurement techniques in healthcare and waste to energy plants. Dr Petridis' current works are focused on forest supply chain and production and distribution of forest products, and energy forms produced from biomass and fossil fuel co-firing. Moreover, one of the fields he is currently working on is the integration of several operational research techniques in an algorithmic way for ranking, forecasting, and decision making with multiple criteria (multi-objective programming). His educational interests are concentrated in optimization and simulation software emphasized in industrial production and planning and his research has been published in international journals and book chapters.

Vincent Charles, PhD, PDRF, FRSS, FHEA, FPPBA, MIScT, CMBE, is an Associate Professor of AI for Business and Director of PGR Studies at the School of Management, University of Bradford. In addition, he holds multiple visiting professorship positions across the Globe. He is an experienced researcher in the fields of AI/ML, (big) data science, and OR/MS. He has more than 25 years of teaching, research, and consultancy experience, having been a full professor and director of research for more than a decade in triple-crown business schools. He is a former Elected Member of the Senate. He holds Executive Certificates from the MIT, HBS, and IE Business School. He has published over 150 research outputs and is a recipient of many international academic honours and awards. AWS Certified Cloud Practitioner, AWS Accredited Educator, Certified Six Sigma Black Belt, and Advance HE Certified External Examiner, UK. He is the Editor in Chief of the International Journal of Business and Emerging Markets, as well as an Associate Editor of the Journal of the Operational Research Society, Expert Systems with Applications, Machine Learning with Applications, Intelligent Systems with Applications, and Decision Analytics Journal. He also has industry experience as a Chief Analytics Officer and has worked on projects in the telecommunications and retail industries.

From the Back Cover

This book provides a comprehensive and practical introduction to Data Envelopment Analysis (DEA). It explains how this non-parametric technique is used to measure performance and extract efficiency from homogeneous entities within a production procedure. It situates DEA within a growing field of productivity analysis and performance measurement, for which numerous models have been proposed. 

This book encapsulates all of the advances in DEA models proposed in the literature. These models are presented in the context of the GAMS software, which is a powerful tool for mathematical programming models. This book serves two educational purposes: it introduces readers to DEA models and provides examples using GAMS. In addition, the reader is introduced to GAMS programming, as well as innovative and practical applications. GAMS codes are available for free, allowing readers to test and expand the models to meet their specific needs.

Edition details

• Publisher: Springer
• Publication date: 2024
• ISBN 10: 3031307038
• ISBN 13: 9783031307034
• Binding: Paperback
• Language: English
• Number of pages: 168